Terminology and Concepts
| SQL Terms/Concepts | MongoDB Terms/Concepts |
|---|---|
| database | database |
| table | collection |
| row | document or BSON document |
| column | field |
| index | index |
| table joins | $lookup, embedded documents |
| primary key Specify any unique column or column combination as primary key. |
In MongoDB, the primary key is automatically set to the _idfield. |
| aggregation (e.g. group by) | aggregation pipeline See the SQL to Aggregation Mapping Chart. |
| transactions | TIP For many scenarios, the denormalized data model (embedded documents and arrays) will continue to be optimal for your data and use cases instead of multi-document transactions. That is, for many scenarios, modeling your data appropriately will minimize the need for multi-document transactions. |
create and alter
| SQL Schema Statements | MongoDB Schema Statements |
|---|---|
CREATE TABLE people (
id MEDIUMINT NOT NULL
AUTO_INCREMENT,
user_id Varchar(30),
age Number,
status char(1),
PRIMARY KEY (id)
)
|
Implicitly created on first db.people.insertOne( {
user_id: "abc123",
age: 55,
status: "A"
} )
However, you can also explicitly create a collection: db.createCollection("people")
|
ALTER TABLE people ADD join_date DATETIME |
Collections do not describe or enforce the structure of its documents; i.e. there is no structural alteration at the collection level. However, at the document level, db.people.updateMany(
{ },
{ $set: { join_date: new Date() } }
)
|
ALTER TABLE people DROP COLUMN join_date |
Collections do not describe or enforce the structure of its documents; i.e. there is no structural alteration at the collection level. However, at the document level, db.people.updateMany(
{ },
{ $unset: { "join_date": "" } }
)
|
CREATE INDEX idx_user_id_asc ON people(user_id) |
db.people.createIndex( { user_id: 1 } )
|
CREATE INDEX
idx_user_id_asc_age_desc
ON people(user_id, age DESC)
|
db.people.createIndex( { user_id: 1, age: -1 } )
|
DROP TABLE people |
db.people.drop() |
Insert
| SQL INSERT Statements | MongoDB insertOne() Statements |
|---|---|
INSERT INTO people(user_id,
age,
status)
VALUES ("bcd001",
45,
"A")
|
db.people.insertOne(
{ user_id: "bcd001", age: 45, status: "A" }
) |
Select
| SQL SELECT Statements | MongoDB find() Statements |
|---|---|
SELECT * FROM people |
db.people.find() |
SELECT id,
user_id,
status
FROM people
|
db.people.find(
{ },
{ user_id: 1, status: 1 }
)
|
SELECT user_id, status FROM people |
db.people.find(
{ },
{ user_id: 1, status: 1, _id: 0 }
)
|
SELECT * FROM people WHERE status = "A" |
db.people.find(
{ status: "A" }
)
|
SELECT user_id, status FROM people WHERE status = "A" |
db.people.find(
{ status: "A" },
{ user_id: 1, status: 1, _id: 0 }
)
|
SELECT * FROM people WHERE status != "A" |
db.people.find(
{ status: { $ne: "A" } }
)
|
SELECT * FROM people WHERE status = "A" AND age = 50 |
db.people.find(
{ status: "A",
age: 50 }
)
|
SELECT * FROM people WHERE status = "A" OR age = 50 |
db.people.find(
{ $or: [ { status: "A" } , { age: 50 } ] }
)
|
SELECT * FROM people WHERE age > 25 |
db.people.find(
{ age: { $gt: 25 } }
)
|
SELECT * FROM people WHERE age < 25 |
db.people.find(
{ age: { $lt: 25 } }
)
|
SELECT * FROM people WHERE age > 25 AND age <= 50 |
db.people.find(
{ age: { $gt: 25, $lte: 50 } }
)
|
SELECT * FROM people WHERE user_id like "%bc%" |
db.people.find( { user_id: /bc/ } )
-or- db.people.find( { user_id: { $regex: /bc/ } } )
|
SELECT * FROM people WHERE user_id like "bc%" |
db.people.find( { user_id: /^bc/ } )
-or- db.people.find( { user_id: { $regex: /^bc/ } } )
|
SELECT * FROM people WHERE status = "A" ORDER BY user_id ASC |
db.people.find( { status: "A" } ).sort( { user_id: 1 } )
|
SELECT * FROM people WHERE status = "A" ORDER BY user_id DESC |
db.people.find( { status: "A" } ).sort( { user_id: -1 } )
|
SELECT COUNT(*) FROM people |
db.people.count() or db.people.find().count() |
SELECT COUNT(user_id) FROM people |
db.people.count( { user_id: { $exists: true } } )
or db.people.find( { user_id: { $exists: true } } ).count()
|
SELECT COUNT(*) FROM people WHERE age > 30 |
db.people.count( { age: { $gt: 30 } } )
or db.people.find( { age: { $gt: 30 } } ).count()
|
SELECT DISTINCT(status) FROM people |
db.people.aggregate( [ { $group : { _id : "$status" } } ] )
or, for distinct value sets that do not exceed the BSON size limit db.people.distinct( "status" ) |
SELECT * FROM people LIMIT 1 |
db.people.findOne() or db.people.find().limit(1) |
SELECT * FROM people LIMIT 5 SKIP 10 |
db.people.find().limit(5).skip(10) |
EXPLAIN SELECT * FROM people WHERE status = "A" |
db.people.find( { status: "A" } ).explain() |
Update Records
| SQL Update Statements | MongoDB updateMany() Statements |
|---|---|
UPDATE people SET status = "C" WHERE age > 25 |
db.people.updateMany(
{ age: { $gt: 25 } },
{ $set: { status: "C" } }
)
|
UPDATE people SET age = age + 3 WHERE status = "A" |
db.people.updateMany(
{ status: "A" } ,
{ $inc: { age: 3 } }
) |
Delete Records
| SQL Delete Statements | MongoDB deleteMany() Statements |
|---|---|
DELETE FROM people WHERE status = "D" |
db.people.deleteMany( { status: "D" } )
|
DELETE FROM people |
db.people.deleteMany({}) |